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Selected Works of Steven Walczak
Article
Universal versus contextual effects on TQM: a triangulation study using neural networks
Production Planning & Control (2017)
  • Steven Walczak, University of South Florida
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Abstract
The objective of this study is to extend previous research on total quality management (TQM)-contextperformance
relationships and ‘fit’ using multiple methods. We combine artificial neural networks
(ANNs) with structural equation modelling (SEM) to analyse several hypotheses and propositions. This is
the first study in this area of research that utilises ANNs and a triangulation technique in the presence
of several contextual factors. The SEM analyses suggest that company size and industry type may have
contingency effects on some of the TQM practices and/or TQM-performance relationships. However, the
ANN models have shown that these two contingency factors do not moderate TQM outcomes, implying
that all organisations can benefit from TQM regardless of size and type. As well, these models show that
formal TQM implementation and/or ISO certifications do not add any predictive power to the ANN models
except in one case: TQM implementation and/or ISO certification added to organisational effectiveness
and customer results to predict financial and market (F&M) results. The results further indicate that even
though implementing TQM alone has a bigger impact on F&M results than obtaining ISO certification
alone, combining the two will have an even greater impact on these results. Joint implementation leads
to greater improvements in organisational effectiveness, which, in turn, has a positive effect on customer
results and consequently F&M results. This is a unique finding within the context of moderator effects on
TQM-performance relationships.
Keywords
  • Total quality management,
  • contextual factors,
  • business results,
  • artificial neural networks,
  • structural equation modeling,
  • survey
Disciplines
Publication Date
2017
DOI
10.1080/09537287.2017.1296598
Citation Information
Steven Walczak. "Universal versus contextual effects on TQM: a triangulation study using neural networks" Production Planning & Control Vol. 28 Iss. 5 (2017) p. 367 - 386
Available at: http://works.bepress.com/steven-walczak/72/